- Computational Biology and Bioinformatics
- Cancer Transcriptome
- Biomarker Identification
- Post-transcriptional Regulation
- Drug Sensitivity Prediction
- Machine Learning
- Network-based Learning
- Semi-supervised Learning
- Reinforcement Learning
- Transfer Learning
- Research Associate, University of Minnesota-Twin Cities (2015-2017)
- Research Intern, Takeda Pharmaceuticals Company (2014)
- ACM-BCB 2019 Workshop Chair
- Program Committee Member: ICDM 2018, 2019, ACM-BCB 2018, 2019, ICCABS 2017
- NSF panel member (2018)
- Reviewers for Nucleic Acids Research, Bioinformatics, PLoS One, BMC Bioinformatics, BMC Genomics, and others
Honors & Awards
- NSF CRII (2018)
- Best Poster Award, The 6th Annual Biomedical Informatics and Computational Biology Research Symposium (2014)
- Jae-Woong Chang*, Wei Zhang*, Hsin-Sung Yeh, et al. An Integrative Model for Alternative Polyadenylation, IntMAP, Delineates mTOR-modulated Endoplasmic Reticulum Stress Response. Nucleic Acids Research, 2018.
- Wei Zhang, Jeremy Chien, Jeongsik Yong, and Rui Kuang. Network-based Machine Learning and Graph Algorithms for Precision Oncology. npj Precision Oncology, 2017.
- Jae-Woong Chang*, Wei Zhang*, Hsin-Sung Yeh, et al. mRNA 3’UTR Shortening is a Molecular Signature of mTORC1 Activation. Nature Communications, 2015.
- Wei Zhang, Takayo Ota, et al. Network-based Survival Analysis Reveals Subnetwork Signatures for Predicting Outcomes of Ovarian Cancer Treatment. PLoS Comput Biol, 2013.